Telecare Service Challenge: Conflict Detection

Telecare and telehealth system services can be dynamically configured to collect, analyse, store, and adapt to multimodal data about people as they go about their activities of daily life. These services need to be able to personalise to subjects and adapt to changes in lifestyles, environments and technology. Such dynamic adaptability may be well supported by a low-level rule programming approach; however measures may need to be taken to limit the emergence of conflicts between the distributed rulesets owing to differing programmatic assumptions and unexpected changes. Here, we consider types of conflict that might arise when a variety of care devices are brought together and begin to rely on each others' services. This paper describes a distributed rule-based conflict detection approach for use with heterogeneous mobile and home care devices. We propose methods that make it possible to detect certain forms of rule conflict. To do so, we introduce Event Calculus based logic for writing device rules and an analytical framework for conflict detection

Coding Human-Animal Interactions in Homes of Children with Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a developmental disorder characterized by differences in social functioning, communication, sensory preferences, and behavior. These differences invite an effort to understand the human-animal bond and its impact on families and children with ASD. The purpose of this study was to determine if the Observation of Human-Animal Interaction for Research (OHAIRE) coding tool can be utilized in a home-based setting to code human-animal interactions in children with ASD. The OHAIRE is a coding tool developed to quantify the behavior of children when interacting with social partners and animals in naturalistic settings. The tool has been tested for reliability and validity within structured, community-based settings; however, it has not been used in home-based settings. This study aimed to analyze the feasibility of utilizing the OHAIRE tool in home-based settings. The second aim was to determine if interrater and intrarater reliability could be reached between coders using data from the home-based videos. Nine minutes of video were obtained for the study. Participant-provided video was challenging to obtain and presented some coding challenges as quality differed from training videos. Participant training and incentives may increase usability of home-based video for coding interactions. Interrater reliability agreement was reached between primary and secondary coders ranging from .842 to .888. Intrarater reliability was met with substantial agreement to almost perfect agreement and ranged from .792 to .929. The OHAIRE coding tool is a promising measure of in-home human-animal interactions that may require adaptations for coding home-based interactions. Further research should include testing in home-based settings with larger and more diverse sample sizes

Preference Elicitation and Reasoning While Smart Shifting of Home Appliances

AbstractA crucial part of the total electricity demand is energy consumption in the residential sector. In parallel to optimizing energy consumption within houses, user comfort is still an essential success criterion for automated solutions used within the house. Choosing the most comfortable appliance schedule is often a challenging task for the members of the house. To bring focus on this challenge, residential customer involvement is enhanced by a trend towards automation of appliances. This trend is reflected by pilot projects such as Linear which uses automated smart appliances at the demand side to attain more flexibility in the electricity system. Moreover, industrial interest from the Telecom, energy and household appliance sector to promote smart schedules for appliances is growing. To meet this trend, this paper describes new ways to model and reason with the user preferences when scheduling appliances in a household under dynamic pricing schemes given different user preferences. These methods have been proven to be efficient in eliciting and computing the user preferences to increase the user comfort in the house

Accessing Data: Methods for understanding mobile technology use

Mobile devices, applications and services have become integrated into people’s dailylives on a personal and professional level. Although traditional research methods arebeing used to understand the use of mobile devices and applications, methodologicalchallenges still exist. Researchers have responded to these challenges in a variety ofways, with an emphasis on developing methods that enable new ways of accessing,making available and collecting data about mobile technology use. This paper identifies,defines, describes and presents, a preliminary framework for understanding themethodological responses emerging in current Mobile Human Computer Interaction(Mobile HCI) research

A framework for field testing in living lab innovation projects

Within innovation research and, more specifically, living lab projects, a crucial component is to test an innovation in a real-life context with potential end users. Such a field test can validate assumptions by combining insights on behaviour and attitudes towards the innovation. This allows for iterative tailoring of the innovation to the needs and wants of the potential end users. Moreover, relevant insights can be gathered to stop or rescope the innovation project before big investments are made. Although studies indicate that testing innovations (or prototypes) in real-life contexts improves the innovation process, there is no specific framework on how to conduct a field test for an innovation. This is important because, in living lab field tests, users are actively involved in co-creating the solutions, which impacts the operational side of setting up living lab projects. Therefore, within this article, we propose a framework for field testing based on the degree to which it reflects reality and the stage within the living lab process. We distinguish four types of field tests: concept, mock-up, pilot, and go2market field test. Based on this framework, we propose some practical guidelines for setting up living lab field tests

Acquiring in situ training data for context-aware ubiquitous computing applications

Ubiquitous, context-aware computer systems may ultimately enable computer applications that naturally and usefully respond to a user's everyday activity. Although new algorithms that can automatically detect context from wearable and environmental sensor systems show promise, many of the most flexible and robust systems use probabilistic detection algorithms that require extensive libraries of training data with labeled examples. In this paper, we describe the need for such training data and some challenges we have identified when trying to collect it while testing three contextdetection systems for ubiquitous computing and mobile applications. Author Keywords Context-aware, ubiquitous, computing, supervised learning, experience sampling, user interface design ACM Classification Keywords H5.m Information interfaces and presentation (e.g. HCI): Miscellaneous

Developing persuasive interfaces

MSCC Dissertation in Computer EngineeringNowadays, computers are indispensable tools for most people. Since computers’ role is to make everyone’s life easier, systems can be built to be of even more assistance. While today people have to learn how to interact with computers, in the future, instead of having to do that, computer systems will be blended in our everyday things. It is expected that technology will come to a point where it is natural to interact with it like with every other object. Computers have been gaining their space in our lives being considered machines that can do almost anything. This master thesis has the purpose of studying how computers can be used as persuasive technology. To build persuasive systems it is important to know that humans are very different from each other. Given this idea it is of extreme importance that the system is able to determine as much aspects of the surrounding environment as it can, to process that information and interact with people accordingly. To achieve a solution that is effective for this concept, a study of persuasive systems is presented in this document. An architecture was developed in order to provide an infrastructure for the development of persuasive applications. An authoring tool was also implemented in order to allow the creation of context aware persuasive applications by users without programming skills. Furthermore, a persuasive application prototype was developed as proof of concept for this study. Usability tests were performed to analyze if users could successfully create the application prototype, named Smart Bins, using the proposed framework. Further user tests were executed with children, the target users of the application prototype, to evaluate its usability and persuasiveness. A description of the Smart Bins application as well as the results of the user tests are presented in this thesis. The results provide further understanding and new perspectives regarding the use of persuasive technologies as interactive computer products, designed to change people’s habits, therefore helping to improve human’s attitudes and behaviours towards important matters like environmental preservation